A common consequence of many neurological disorders like cerebral palsy, Parkinson's disease or stroke (to name few) is the appearance of atypical biomechanical conditions such as an increase in muscle tone due to active contraction of the muscle at rest, hyperexcitability of motoneurons, excessive coactivation, muscle contractures, etc. In today's clinical practice, it is common to manipulate a patient's limbs to diagnose these abnormal biomechanical changes. Through such physical interaction, clinicians extract as much information as possible to infer the patients' condition and make an educated assessment. These assessments are usually restricted to ordinal rating scales and single joints (e.g. Ashworth, Tardieu, HAT), which is a limitation when inferring the nature and gravity of the impairment since the effect generated by pluri-articular muscles to multi-joint mechanics can be misjudged. A misjudgment on the initial or intermediate assessments can lead to selecting a non-optimal intervention, which can have negative consequences, such as increasing intervention time, rising in treatment cost, or even worsening the condition. Hence, the capability to discriminate between different types and levels of abnormal biomechanics is important for the clinical intervention to be chosen and planned accordingly.
Traditional engineering approaches such as system-identification techniques provide a less subjective, quantitative measure of biomechanical variables, which are instrumental to assess differences in limb mechanics. A first limitation of such approaches is that these require the use of sophisticated measurement systems, such as stiff robotic devices, making most of these classical engineering methods impractical for the clinical setting do to a high cost/benefit ratio. A second limitation in the prior art is that these have been limited to single joints (e.g. knee, ankle, elbow) as more complex joints (e.g. shoulder) pose significant challenges. Yet, abnormal biomechanics after neurological disorders can encompass alteration of inter-muscular (heteronymous) reflexes or abnormal multi-joint couplings. A third limitation, is that the prior art fails to teach or suggest the diagnosis or treatment of abnormal biomechanics to the clinician. In the attempt to understand how limbs affected by different forms of hypertonia are perceived by the clinicians when being manipulated, researchers have tried to haptically reproduce the physical impairment of stroke survivors via robotic prototypes. Such approaches however, are still limited to only one degree of freedom (DOF) and focus on mimicking current techniques, such as the Ashworth test. Providing a method to enable therapists to appreciate and quantify abnormal limb biomechanics can lead to better training and improved classification, measurement, and treatment of these disorders.